What is a data scientist?

Harvard was the first to say “data scientists” is the sexiest job of the 21st Century. 

The field of data science is an interdisciplinary field that uses scientific methods, processes, algorithms and leverages diverse systems to extract knowledge and insights from many structural and unstructured data sets. 

Data science is related to data mining, deep learning and big data, and requires a multi-disciplinary skillset. What is key is translating data insights into value-based messages that business leaders can appreciate and move to action. Having a strong blend of statistics, analytics and technology skills vary widely, but strong data scientist profiles demonstrate skills related to problem-solving in the workplace, including soft skills such as communication, creativity and teamwork. 

Having the blend of these skills is often hard to find, and the T shaped individuals who have both strong technical and communication and cross-functional knowledge domain skills are in fierce demand. 

Meet Carol Wilson, Director of Advanced Analytics at Canada Post

Carol is the Director of Advanced Analytics at Canada Post Corporation and reports into the Business Intelligence and Analytics Group under a Strategy VP. In her role, she leads a team of seven data scientists who are responsible for providing the business with data-driven answers to their business questions. They work on hundreds of projects throughout a year, and usually have two to three major transformational programs to keep them all challenged.

This can involve simple queries of large data sets that take a few minutes to machine learning models that can take months to develop. Carol currently specializes in statistics and research methods, presenting advanced techniques using AI for decision trees and time series analysis to discover relevancy to business leaders at Canada Post to solve complex problems.

A Little About Canada Post

Canada Post provides postal services to more than sixteen million addresses and delivers annually over eight billion items and revenues are approaching eight billion. Delivery takes place via traditional “to the door” service and centralized delivery by twenty-five thousand letter carriers, through a thirteen thousand vehicle fleet. Securing economies of scale to balance supply and demand in a complex logistics system is a constant focus of the Canada Post data scientists.

Canada Post is rapidly advancing the use of AI and Data Sciences problem-solving methods to transform how business is done. Challenging research is underway to ensure the company secures the best routes to maximize margin and profitability. Canada Post’s Data Science Team is tackling complex shipping data to secure insightful analytics to improve operational efficiencies etc.

What are the skills that Canada Post data scientists have to solve the complex challenges that require Artificial Intelligence?

Carol’s provided an excellent summary of the foundational skills her data scientists need to be recruited into Canada Post, but also highlights the skills needed to enter in to this field, from different disciplines. The data scientists at Canada Post all have expertise in SAS and SQL. At Canada Post, these skills are mandatory. In addition, they are all skilled in Python and R and are moving toward using these AI data science languages instead of using SQL. 

Canada Post is advancing its data sources to all be in the Cloud and are using the Microsoft Azure Platform offerings. In addition, they have an Enterprise Data Warehouse (EDW) located on a Teradata appliance so understanding Teradata and TD Studio are also skills that the Canada Post data scientists have to learn to do any data extractions to do any advanced modelling. Carol stressed that having skills in advanced statistics, and the importance of strong math, or science, or computing skills. Strong analytical skills are key to becoming a strong data scientist as there is so much data analysis required, a blend of business, data sciences and computing skills provide a strong foundation for building a career as a data scientist.

What did Carol study in school to become a data scientist?

When I interviewed Carol, she stressed as a young teenager, she excelled more in the Arts, in particular, English was a big favorite. When she graduated, she enrolled at Mount Allison University in New Brunswick to first complete a Psychology Degree. Her skills in English were invaluable as she was able to write clearly on her research findings and observations, so the Arts served as an excellent foundation for her to advance into her data science careers. Carol stressed, “If you cannot communicate, all the skills in math and statistics won’t help advance business leaders to take action on the data research insights.” Carol later went on to complete a Master’s Degree in Experimental Psychology from McMaster University in Hamilton.

Learn More:

  • To listen to the full story of Carol Wilson’s journey to become a data scientist and How Canada Post is applying data science, see her on video on SalesChoice’s YouTube Channel here.
  • To listen to the second part of Carol Wilson’s journey to become a data scientist in our blog, click here.
  • You can access additional knowledge on Artificial Intelligence and data sciences by going to SalesChoice’s AI Channel on YouTube or visit our SalesChoice Predictive AI World Forum here. Here you will find white papers, research papers, podcasts, webinar history, etc. to advance your knowledge of AI.
  • You can also go to the AIDirectory.ai and keep track of what’s happening in our AI ecosystem in North America and China, a Joint Venture by ITWC, CATA and SalesChoice Inc.
  • To follow SalesChoice on Twitter, go here.
  • To contact the author, Dr. Cindy Gordon, CEO SalesChoice, you can reach her on LinkedIn
  • To contact Carol Wilson, you can reach her on LinkedIn.